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Artificial Intelligence (AI) is fundamentally transforming the labor market, impacting various job sectors through cognitive AI, machine learning, and deep learning. These technologies enhance productivity and efficiency across industries, including finance, healthcare, and customer service. However, they also pose risks such as job displacement, economic inequality, and ethical dilemmas. This study utilizes a mixed-methods approach, combining quantitative data analysis with qualitative interviews to examine the impact of AI on employment. The research focuses on different AI technologies' effects on various job roles and sectors, highlighting the dichotomy between high-skill and low-skill workers. The findings reveal that AI-driven automation primarily affects low-skill jobs, leading to structural unemployment and increased job insecurity. High-skill workers benefit from productivity gains and new professional roles, while low-skill workers face greater competition and job displacement. The study also highlights the paradox of AI-enhanced efficiency not translating into reduced working hours, particularly in competitive industries. The introduction of AI has not realized John Maynard Keynes' prediction of reduced working hours and increased leisure time. Instead, it has led to longer working hours and continuous upskilling demands. The study underscores the need for regulatory measures to balance AI adoption with the protection of human jobs and rights. Recommendations include job retraining programs, ethical AI development standards, and fair labor practices.
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Qingshuang Song (Fri,) studied this question.
www.synapsesocial.com/papers/68e572c2b6db643587512c9d — DOI: https://doi.org/10.54097/7t0k2573
Qingshuang Song
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